通过整合 RUSLE-SDR-TLA 模型评估印度考弗里河流域的土壤侵蚀情况

IF 2.8 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES Environmental Earth Sciences Pub Date : 2024-09-18 DOI:10.1007/s12665-024-11851-4
Asna Nizar, Upendra Badimela, Ciba Manohar, Jesuraja Kamaraj, Sreenivasulu Ganugapenta, Jayaraju Nadimikeri, Anoop Krishnan
{"title":"通过整合 RUSLE-SDR-TLA 模型评估印度考弗里河流域的土壤侵蚀情况","authors":"Asna Nizar,&nbsp;Upendra Badimela,&nbsp;Ciba Manohar,&nbsp;Jesuraja Kamaraj,&nbsp;Sreenivasulu Ganugapenta,&nbsp;Jayaraju Nadimikeri,&nbsp;Anoop Krishnan","doi":"10.1007/s12665-024-11851-4","DOIUrl":null,"url":null,"abstract":"<div><p>India, a subtropical country, also has relatively more environmental problems because of intense rainfall that occurs quickly, as well as other natural and man-made causes of soil degradation. The use of predictive models in GIS is observed beneficial for computing the virgin net soil erosion as well as deposition. Thus, the study aims to evaluate the spatial long-term average annual soil erosion (gross soil erosion rate), net soil erosion as well as a deposition for the east-flowing Cauvery River Basin (CRB) using RUSLE integrated with the TLA-SDR model in Geographic Information System (GIS) at recent (2020 to 2022) periods. The estimation of gross soil erosion rates (A) ranges between 0 and 94,194.4 t h<sup>−1</sup> year<sup>−1</sup>, mean of ~ 223 t h<sup>−1</sup> year<sup>−1</sup>. The sediment yield (SY) of CRB varies from 0 to 10,895.4 t h<sup>−1</sup> year<sup>−1</sup> with a mean of 26 t h<sup>−1</sup> year<sup>−1</sup>. Moreover, the transport capacity (TC) of CRB varies between 0 and 5,339,136 t h<sup>−1</sup> year<sup>−1</sup>, with a mean of 16 t h<sup>−1</sup> year<sup>−1</sup>. Further, net erosion is estimated with TC and deposition which has an average value of ~ 4.5 t ha<sup>−1</sup> year<sup>−1</sup> (i.e., ~ 2% of the gross erosion), of which 1.15% of CRB shows very severe erosion while 56.68% shows high deposition. The study also addresses the effect of various LULC types on soil loss and reveals that barren rocks have the highest soil loss, followed by forest, build-up, barren land, agricultural land, and plantation. Likewise, the study assesses whether rapid climate change may exacerbate erosion rates and concludes that greater erosion rates are recorded with rising rainfall. Additionally, when comparing the total erosion to total sediment yield rate of CRB with major basins like Ganga (GBA) and Kosi (KB), signifying the topographical, climatic as well as tectonic setup of the region. The study’s findings will be an important tool for decision-makers as they execute management plans over the CRB, and this technique will used broadly to identify management methods in river catchments worldwide.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"83 19","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessment of soil erosion by integrating RUSLE-SDR-TLA model in Cauvery river basin, India\",\"authors\":\"Asna Nizar,&nbsp;Upendra Badimela,&nbsp;Ciba Manohar,&nbsp;Jesuraja Kamaraj,&nbsp;Sreenivasulu Ganugapenta,&nbsp;Jayaraju Nadimikeri,&nbsp;Anoop Krishnan\",\"doi\":\"10.1007/s12665-024-11851-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>India, a subtropical country, also has relatively more environmental problems because of intense rainfall that occurs quickly, as well as other natural and man-made causes of soil degradation. The use of predictive models in GIS is observed beneficial for computing the virgin net soil erosion as well as deposition. Thus, the study aims to evaluate the spatial long-term average annual soil erosion (gross soil erosion rate), net soil erosion as well as a deposition for the east-flowing Cauvery River Basin (CRB) using RUSLE integrated with the TLA-SDR model in Geographic Information System (GIS) at recent (2020 to 2022) periods. The estimation of gross soil erosion rates (A) ranges between 0 and 94,194.4 t h<sup>−1</sup> year<sup>−1</sup>, mean of ~ 223 t h<sup>−1</sup> year<sup>−1</sup>. The sediment yield (SY) of CRB varies from 0 to 10,895.4 t h<sup>−1</sup> year<sup>−1</sup> with a mean of 26 t h<sup>−1</sup> year<sup>−1</sup>. Moreover, the transport capacity (TC) of CRB varies between 0 and 5,339,136 t h<sup>−1</sup> year<sup>−1</sup>, with a mean of 16 t h<sup>−1</sup> year<sup>−1</sup>. Further, net erosion is estimated with TC and deposition which has an average value of ~ 4.5 t ha<sup>−1</sup> year<sup>−1</sup> (i.e., ~ 2% of the gross erosion), of which 1.15% of CRB shows very severe erosion while 56.68% shows high deposition. The study also addresses the effect of various LULC types on soil loss and reveals that barren rocks have the highest soil loss, followed by forest, build-up, barren land, agricultural land, and plantation. Likewise, the study assesses whether rapid climate change may exacerbate erosion rates and concludes that greater erosion rates are recorded with rising rainfall. Additionally, when comparing the total erosion to total sediment yield rate of CRB with major basins like Ganga (GBA) and Kosi (KB), signifying the topographical, climatic as well as tectonic setup of the region. The study’s findings will be an important tool for decision-makers as they execute management plans over the CRB, and this technique will used broadly to identify management methods in river catchments worldwide.</p></div>\",\"PeriodicalId\":542,\"journal\":{\"name\":\"Environmental Earth Sciences\",\"volume\":\"83 19\",\"pages\":\"\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Earth Sciences\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12665-024-11851-4\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Earth Sciences","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s12665-024-11851-4","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

印度是一个亚热带国家,由于降雨量大、降雨速度快以及其他自然和人为原因造成土壤退化,因此环境问题也相对较多。在地理信息系统中使用预测模型有利于计算原始净土壤侵蚀和沉积。因此,本研究旨在利用 RUSLE 与地理信息系统 (GIS) 中的 TLA-SDR 模型的集成,评估最近(2020 年至 2022 年)时期东流考弗里河流域 (CRB) 的空间长期平均年土壤侵蚀量(总土壤侵蚀率)、净土壤侵蚀量以及沉积量。土壤侵蚀总速率(A)的估算值介于 0 到 94,194.4 吨/小时-年-1 之间,平均值约为 223 吨/小时-年-1。CRB 的泥沙产量(SY)介于 0 到 10,895.4 吨/小时-年-1 之间,平均为 26 吨/小时-年-1。此外,中流断面的输运能力(TC)在 0 至 5,339,136 t h-1 year-1 之间变化,平均值为 16 t h-1 year-1。此外,根据 TC 和沉积估算出的净侵蚀量的平均值约为 4.5 吨/公顷-年-1(即约为总侵蚀量的 2%),其中 1.15%的 CRB 侵蚀非常严重,而 56.68%的 CRB 则沉积严重。研究还探讨了各种 LULC 类型对土壤流失的影响,结果表明,荒岩的土壤流失量最大,其次是森林、建筑、荒地、农田和种植园。同样,研究还评估了快速的气候变化是否会加剧土壤侵蚀率,并得出结论:降雨量增加时,土壤侵蚀率也会增加。此外,将 CRB 的总侵蚀率和总沉积物产出率与恒河(Ganga,GBA)和科西(Kosi,KB)等主要流域进行比较,表明了该地区的地形、气候和构造设置。这项研究的结果将成为决策者们执行中断裂带管理计划的重要工具,这项技术也将广泛用于确定全球河流集水区的管理方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Assessment of soil erosion by integrating RUSLE-SDR-TLA model in Cauvery river basin, India

India, a subtropical country, also has relatively more environmental problems because of intense rainfall that occurs quickly, as well as other natural and man-made causes of soil degradation. The use of predictive models in GIS is observed beneficial for computing the virgin net soil erosion as well as deposition. Thus, the study aims to evaluate the spatial long-term average annual soil erosion (gross soil erosion rate), net soil erosion as well as a deposition for the east-flowing Cauvery River Basin (CRB) using RUSLE integrated with the TLA-SDR model in Geographic Information System (GIS) at recent (2020 to 2022) periods. The estimation of gross soil erosion rates (A) ranges between 0 and 94,194.4 t h−1 year−1, mean of ~ 223 t h−1 year−1. The sediment yield (SY) of CRB varies from 0 to 10,895.4 t h−1 year−1 with a mean of 26 t h−1 year−1. Moreover, the transport capacity (TC) of CRB varies between 0 and 5,339,136 t h−1 year−1, with a mean of 16 t h−1 year−1. Further, net erosion is estimated with TC and deposition which has an average value of ~ 4.5 t ha−1 year−1 (i.e., ~ 2% of the gross erosion), of which 1.15% of CRB shows very severe erosion while 56.68% shows high deposition. The study also addresses the effect of various LULC types on soil loss and reveals that barren rocks have the highest soil loss, followed by forest, build-up, barren land, agricultural land, and plantation. Likewise, the study assesses whether rapid climate change may exacerbate erosion rates and concludes that greater erosion rates are recorded with rising rainfall. Additionally, when comparing the total erosion to total sediment yield rate of CRB with major basins like Ganga (GBA) and Kosi (KB), signifying the topographical, climatic as well as tectonic setup of the region. The study’s findings will be an important tool for decision-makers as they execute management plans over the CRB, and this technique will used broadly to identify management methods in river catchments worldwide.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Environmental Earth Sciences
Environmental Earth Sciences 环境科学-地球科学综合
CiteScore
5.10
自引率
3.60%
发文量
494
审稿时长
8.3 months
期刊介绍: Environmental Earth Sciences is an international multidisciplinary journal concerned with all aspects of interaction between humans, natural resources, ecosystems, special climates or unique geographic zones, and the earth: Water and soil contamination caused by waste management and disposal practices Environmental problems associated with transportation by land, air, or water Geological processes that may impact biosystems or humans Man-made or naturally occurring geological or hydrological hazards Environmental problems associated with the recovery of materials from the earth Environmental problems caused by extraction of minerals, coal, and ores, as well as oil and gas, water and alternative energy sources Environmental impacts of exploration and recultivation – Environmental impacts of hazardous materials Management of environmental data and information in data banks and information systems Dissemination of knowledge on techniques, methods, approaches and experiences to improve and remediate the environment In pursuit of these topics, the geoscientific disciplines are invited to contribute their knowledge and experience. Major disciplines include: hydrogeology, hydrochemistry, geochemistry, geophysics, engineering geology, remediation science, natural resources management, environmental climatology and biota, environmental geography, soil science and geomicrobiology.
期刊最新文献
Assessing the performance of machine learning models for predicting soil organic carbon variability across diverse landforms Geostatistical analysis and interpretation of Ilesha aeromagnetic data south–western, Nigeria Application of remote sensing image processing based on artificial intelligence in landscape pattern analysis ResNet50 in remote sensing and agriculture: evaluating image captioning performance for high spectral data Research on microstructure and porosity calculation of rammed soil modified by lime-based materials: the case of rammed earth of pingyao city wall, a world heritage site
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1